An explainable machine learning framework for early student dropout risk prediction and stratification
Student dropout remains a persistent challenge in higher education institutions, affecting academic continuity, institutional performance, and long-term socioeconomic outcomes. Early identification of at-risk students enables timely intervention and improved retention strategies. This study proposes an explainable mach...